Hightide-video

"HighTide-Video: A Novel Framework for Real-time Video Analysis and Understanding using Multimodal Fusion and Temporal Graph Learning"

In this paper, we propose HighTide-Video, a novel framework for real-time video analysis and understanding that leverages multimodal fusion and temporal graph learning. Our framework provides a comprehensive understanding of video content by integrating multiple modalities and modeling temporal relationships between video frames. Experimental results demonstrate the effectiveness of HighTide-Video in various video analysis tasks. Future work includes exploring more advanced multimodal fusion strategies and applying HighTide-Video to more practical applications. HighTide-Video

Videos are a rich source of information, containing not only visual data but also audio and text information. However, traditional video analysis methods often focus on visual features, neglecting the importance of audio and text modalities. Moreover, these methods typically rely on simplistic features and do not account for the complex temporal relationships between video frames. Recent advances in multimodal fusion and temporal graph learning have shown great promise in improving video analysis performance. In this paper, we propose HighTide-Video, a novel framework that integrates multimodal fusion and temporal graph learning for real-time video analysis and understanding. Our framework integrates multiple modalities

The increasing availability of video data has led to a growing demand for efficient and accurate video analysis techniques. However, traditional video analysis methods often rely on simplistic features and neglect the complex relationships between different modalities (e.g., visual, audio, and text). In this paper, we propose HighTide-Video, a novel framework for real-time video analysis and understanding that leverages multimodal fusion and temporal graph learning. Our framework integrates multiple modalities, including visual, audio, and text features, to provide a comprehensive understanding of video content. We design a temporal graph learning module to model the temporal relationships between video frames and capture long-range dependencies. Experimental results on several benchmark datasets demonstrate the effectiveness of HighTide-Video in various video analysis tasks, including video classification, object detection, and sentiment analysis. and text features

We will release the code and data for HighTide-Video to facilitate reproducibility and encourage further research in this area.